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R package arulesViz - Visualizing Association Rules and Frequent Itemsets

CRAN version stream r-universe status CRAN RStudio mirror downloads

Introduction

This R package extends package arules with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration.

The following R packages use arulesViz: arules, fdm2id, rattle, TELP

To cite package ‘arulesViz’ in publications use:

Hahsler M (2017). “arulesViz: Interactive Visualization of Association Rules with R.” R Journal, 9(2), 163-175. ISSN 2073-4859, doi:10.32614/RJ-2017-047 https://doi.org/10.32614/RJ-2017-047, https://journal.r-project.org/archive/2017/RJ-2017-047/RJ-2017-047.pdf.

@Article{,
  title = {arules{V}iz: {I}nteractive Visualization of Association Rules with {R}},
  author = {Michael Hahsler},
  year = {2017},
  journal = {R Journal},
  volume = {9},
  number = {2},
  pages = {163--175},
  url = {https://journal.r-project.org/archive/2017/RJ-2017-047/RJ-2017-047.pdf},
  doi = {10.32614/RJ-2017-047},
  month = {December},
  issn = {2073-4859},
}

This might also require the development version of arules.

Features

Available Visualizations

Installation

Stable CRAN version: Install from within R with

install.packages("arulesViz")

Current development version: Install from r-universe.

install.packages("arulesViz",
    repos = c("https://mhahsler.r-universe.dev". "https://cloud.r-project.org/"))

Usage

Mine some rules.

library("arulesViz")
data("Groceries")
rules <- apriori(Groceries, parameter = list(support = 0.005, confidence = 0.5))
## Apriori
## 
## Parameter specification:
##  confidence minval smax arem  aval originalSupport maxtime support minlen
##         0.5    0.1    1 none FALSE            TRUE       5   0.005      1
##  maxlen target  ext
##      10  rules TRUE
## 
## Algorithmic control:
##  filter tree heap memopt load sort verbose
##     0.1 TRUE TRUE  FALSE TRUE    2    TRUE
## 
## Absolute minimum support count: 49 
## 
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[169 item(s), 9835 transaction(s)] done [0.00s].
## sorting and recoding items ... [120 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 done [0.00s].
## writing ... [120 rule(s)] done [0.00s].
## creating S4 object  ... done [0.00s].

Standard visualizations

plot(rules)

plot(rules, method = "graph", limit = 20)

Interactive visualization

Live examples for interactive visualizations can be seen in Chapter 5 of An R Companion for Introduction to Data Mining

References

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.